Activate AI
Most AI initiatives stall between pilot and production. We help you close that gap.
The question most organisations are asking is not whether to use AI but why they cannot get it out of the lab and into the business. The answer almost always comes back to data: data that is not trusted, not governed, not moving fast enough, or not structured in a way that AI can reliably work with.
Moving AI from experimentation into production requires more than a good model. It requires a data foundation that AI can actually depend on – clean, governed, and capable of supporting transactional, analytical, and vector workloads simultaneously. It requires governance that keeps AI compliant and controllable as it scales. And it requires the orchestration that connects AI to the workflows and business processes where it creates measurable value. That is what we build.
The data platform your AI can actually rely on
Most existing data platforms were not designed with AI in mind. They may separate transactional and analytical workloads but cannot handle vector search, and struggle to deliver the query performance production AI demands.
We build and migrate to platforms that handle all three workload types simultaneously, using SingleStore for unified operational and analytical performance, DataStax for unstructured data and vector search, and IBM watsonx.data as the governed lakehouse layer across the estate.
AI agents that work in production, not just in demos
AI agents, systems that take actions and coordinate across tools and workflows rather than simply generating answers, are moving rapidly from concept to enterprise deployment. Getting them into production safely means connecting them to reliable, governed data, building the orchestration that lets them interact with business systems, and establishing the controls that keep them compliant and auditable.
We deploy AI agents using IBM watsonx Orchestrate, with IBM watsonx.governance providing the oversight and risk management that scales with adoption.
Scaling AI across the organisation, not just within it
Isolated AI successes are common. Scaling them is where most programmes stall because production at enterprise scale surfaces requirements that pilots never reveal: edge cases in the data, integration complexity, performance at real volumes, and governance demands that grow with every new use case.
We approach operational AI enablement as a programme rather than a project: sequenced to create early production value while building toward the coherent, governed AI capability that delivers sustained results.
Every project we deliver is built on data you can trust.
AI is only as trustworthy as the data it runs on. Governance, security, and data quality are not constraints on AI ambition, they are what makes production AI possible.
That means knowing what sensitive data you have and where it lives. It means protecting it as it moves – through masking, archiving, and controlled access at every stage of its lifecycle. And it means ensuring that the data feeding your analytics and AI is catalogued, traceable, and genuinely reliable before you depend on it.
Find out more about our data security and governance capabilities >
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If your AI initiative has stalled, there is usually a reason. And it is usually fixable.
Start with a conversation. We will help you identify where the real constraint is and what a clear path forward looks like.